Plotting using Matplotlib

The Purpose of Matplotlib

Matplotlib is a Python library used to create static, animated, and interactive 2D plots or figures. It is the standard tool for data visualisation in Python. To install it, you run the following command from your command prompt:

pip install matplotlib

Once installed, you need to import its pyplot module before you can start plotting. The standard way to do this is:

import matplotlib.pyplot as plt

Here, plt is an alias (a short alternative name) for matplotlib.pyplot. You can choose any alias you like, but plt is the convention used by almost all Python programmers.

Understanding the Components of a Plot

The pyplot module contains a collection of functions that let you build and modify a plot step by step. The central function is plot(), which creates a figure. A figure is the overall window or canvas where everything is drawn. Inside a figure, you will find several components:

• A plotting area (the actual chart)
• Axis labels (descriptions for the x-axis and y-axis)
• Ticks (the small marks along the axes that show scale)
• A title (a heading for the chart)
• A legend (a key that explains what different lines or markers represent)

Each function in pyplot makes a specific change to the figure. For example, one function creates the figure, another creates the plotting area, another plots lines, and others add labels or a title.

The Importance of Clear Presentation

When you present data through charts, it is essential that the information is easily understood. Therefore, you should always:

• Give the chart a clear title
• Label both the x-axis and y-axis
• Provide a legend if you have more than one set of data plotted

Basic Plotting: x versus y

To plot one set of values against another, you write:

plt.plot(x, y)

Here, x is the list of values for the horizontal axis, and y is the list of values for the vertical axis. After you have created the plot, you must call plt.show() to display the figure on your screen.

A Worked Example: Temperature Over Three Days

Consider a city where the maximum temperature is recorded for three consecutive days. The following program demonstrates how to plot these temperature values:

import matplotlib.pyplot as plt

# List storing dates in string format
date = ["25/12", "26/12", "27/12"]

# List storing temperature values
temp = [8.5, 10.5, 6.8]

# Create a figure plotting temperature versus date
plt.plot(date, temp)

# Show the figure
plt.show()

In this program, plot() is given two parameters. The first parameter (date) provides the values for the x-axis, and the second parameter (temp) provides the values for the y-axis. The x and y ticks are displayed automatically based on the data you provide.

By default, the plot() function draws a line chart, as shown in the output of this program.

Saving a Plot

You can save the figure you have created in two ways:

1. Manually: Click the save button on the output window that appears when you run plt.show().
2. Programmatically: Use the savefig() function. Pass the desired filename (including the extension) as a parameter. For example: plt.savefig('x.png')

This saves the plot as an image file in your current working directory.

Different Types of Plots

The plot() function is just one of many plotting methods available in pyplot. The choice of plot depends on the type of data you have. The table below lists the main functions for creating different kinds of charts: …